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In this paper, we introduce a tensor neural network based machine learning method for solving the elliptic partial differential equations with random coefficients in a bounded physical domain. With the help of tensor product structure, we…

Numerical Analysis · Mathematics 2024-02-02 Hongtao Chen , Rui Fu , Yifan Wang , Hehu Xie

This paper is devoted to the study of some nonlinear parabolic equations with discontinuous diffusion intensities. Such problems appear naturally in physical and biological models. Our analysis is based on variational techniques and in…

Analysis of PDEs · Mathematics 2021-02-09 Dohyun Kwon , Alpár Richárd Mészáros

We present a robust and accurate numerical method for the anisotropic diffusion equation in curvilinear coordinates. This study extends the recent work [Muir et al., Computer Physics Communications, 2025] for solving the anisotropic…

Numerical Analysis · Mathematics 2026-04-23 Dean Muir , Kenneth Duru , Stuart Hudson , Matthew Hole

With the increasing use of ultrashort laser pulses and nanoscale-materials, one is regularly confronted to situations in which the properties of the media supporting propagation are not varying slowly with time (or space). Hence, the usual…

Other Condensed Matter · Physics 2009-11-10 Guillaume Petite , Alexander Shvartsburg

This paper provides the semi-discrete scheme by the central local discontinuous Galerkin method for space fractional diffusion equation on two sets of overlapping cells, and then we give the stability analysis and error estimates for the…

Numerical Analysis · Mathematics 2019-08-05 Jing Sun , Daxin Nie , Weihua Deng

We devise a stabilized method to weakly enforce bound constraints in the discrete solution of advection-dominated diffusion problems. This method combines a nonlinear penalty formulation with a discontinuous Galerkin-based residual…

Numerical Analysis · Mathematics 2020-11-24 Roberto J. Cier , Sergio Rojas , Victor M. Calo

Purpose: To facilitate the implementation/validation of signal representations and models using parametric matrix-variate distributions to approximate the diffusion tensor distribution (DTD) $\mathcal{P}(\mathbf{D})$. Theory: We establish…

Computational Engineering, Finance, and Science · Computer Science 2020-05-25 A. Reymbaut

In this paper, we propose a method for the approximation of the solution of high-dimensional weakly coercive problems formulated in tensor spaces using low-rank approximation formats. The method can be seen as a perturbation of a minimal…

Numerical Analysis · Mathematics 2015-02-13 Marie Billaud-Friess , Anthony Nouy , Olivier Zahm

In this paper we show that visual diffusion models can serve as effective geometric solvers: they can directly reason about geometric problems by working in pixel space. We first demonstrate this on the Inscribed Square Problem, a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Nir Goren , Shai Yehezkel , Omer Dahary , Andrey Voynov , Or Patashnik , Daniel Cohen-Or

We present recent finite element numerical results on a model convection-diffusion problem in the singular perturbed case when the convection term dominates the problem. We compare the standard Galerkin discretization using the linear…

Numerical Analysis · Mathematics 2023-02-16 Constantin Bacuta , Daniel Hayes , Tyler O'Grady

The functional distributions of particle trajectories have wide applications, including the occupation time in half-space, the first passage time, and the maximal displacement, etc. The models discussed in this paper are for characterizing…

Numerical Analysis · Mathematics 2017-07-27 Zhijiang Zhang , Weihua Deng

In this paper, we present a sparse grid-based Monte Carlo method for solving high-dimensional semi-linear nonlocal diffusion equations with volume constraints. The nonlocal model is governed by a class of semi-linear partial…

Numerical Analysis · Mathematics 2025-07-08 Changtao Sheng , Bihao Su , Chenglong Xu

In this paper a numerical procedure to simulate low diffusivity scalar turbulence is presented. The method consists of using a grid for the advected scalar with a higher spatial resolutions than that of the momentum. The latter usually…

Long simulation times in climate sciences typically require coarse grids due to computational constraints. Nonetheless, unresolved subscale information significantly influences the prognostic variables and can not be neglected for reliable…

Numerical Analysis · Mathematics 2018-02-22 Konrad Simon , Jörn Behrens

The present work addresses the Cauchy problem for an abstract nonlinear system of coupled hyperbolic equations associated with the Timoshenko model in a real Hilbert space. Our purpose is to develop and delve into a temporal discretization…

Numerical Analysis · Mathematics 2026-02-24 Jemal Rogava , Zurab Vashakidze

A discontinuous Galerkin (dG) method for the numerical solution of initial/boundary value multi-compartment partial differential equation (PDE) models, interconnected with interface conditions, is presented and analysed. The study of…

Numerical Analysis · Mathematics 2013-04-16 Andrea Cangiani , Emmanuil H. Georgoulis , Max Jensen

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the…

Numerical Analysis · Computer Science 2012-04-30 Dohy Hong

A method is developed within an adaptive framework to solve quasilinear diffusion problems with internal and possibly boundary layers starting from a coarse mesh. The solution process is assumed to start on a mesh where the problem is badly…

Numerical Analysis · Mathematics 2016-02-16 Sara Pollock

In this paper, we develop a Bernstein dual-Petrov-Galerkin method for the numerical simulation of a two-dimensional fractional diffusion equation. A spectral discretization is applied by introducing suitable combinations of dual Bernstein…

Numerical Analysis · Mathematics 2017-05-16 Mostafa Jani , Shahnam Javadi , Esmail Babolian , Dambaru Bhatta

Diffusion models have recently emerged as a powerful technique in image generation, especially for image super-resolution tasks. While 2D diffusion models significantly enhance the resolution of individual images, existing diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Bohao Chen , Yanchao Zhang , Yanan Lv , Hua Han , Xi Chen
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